Advancements based on fuzzy regression model based on interval-valued fuzzy neural network and its applications to management

Regression is a fundamental component of data analysis and artificial intelligence that acts as a building block for this field. However, comprehensive lacks the development of regression models for interval-valued data that can be done as factors influencing these sets. In this paper, a fuzzy regression model based on an interval-valued fuzzy neural network and its applications to management is analyzed. We investigated some fuzzy regression models with type-1 and type-2 fuzzy regressions, namely IV-T1FR and IV-T2FR. The interval-valued fuzzy neural network (IVFNN) could be trained with clear and interval-valued fuzzy data. Here a neural network was considered as a method for analyzing and forecasting earned value schedule. This article introduces models based on interval fuzzy rule-based modeling (iFRB) and its application in management. Finally, we analyzed the affecting of this method and compared this method with existing methods.

Advancements based on fuzzy regression model based on interval-valued fuzzy neural network and its applications to management Keywords:

Regression , interval-valued fuzzy , neural network